Success of computerized ultrasonic tomography depends upon whether stable and computationally efficient digital ray tracing algorithms can be developed. The need for ray tracing arises from the fact that in computerized tomographic imaging it is essential to know paths of propagation of energy (rays) from their source to detectors. While with x-ray these paths are always straight lines, with ultrasound they are curved and tissue dependent. We at Purdue University have recently proposed two new algorithms for digital ray tracing. One of these is based on the method of chracteristics, while the other used linearization of the eikonal equation. The aim of the research effort outlined in this proposal is to do a detailed study of the digital ray tracing algorithms from the following standpoints: 1) Their ability to trace rays in the presence of measurement and reconstruction noise; the reconstruction noise is generated by using only a finite number of projections and rays in each projection for reconstruction. 2) Their dependence on the sampling density in the reconstructed tomograms. 3) Their dependence on the number of quantization levels used for image reconstruction. 4) Their computational efficiency and also their adaptability real time processing.